The present invention relates to a video signal encoding/decoding method, and more particularly, to a prediction method for discrete cosine transform coefficients, for predicting a DC coefficient using the maximum and minimum values of adjacent blocks.
A discrete cosine encoder encodes without loss a DC coefficient which is a coefficient obtained after quantization. Here, the DC prediction in a discrete cosine transform domain is to predict DC coefficients among adjacent blocks. A lossless encoder/decoder using the prediction of DC coefficients obtained after discrete cosine transform (DCT) quantization is shown in FIG. 3.
FIG. 1 is a diagram illustrating a conventional DC coefficient prediction method. Suppose that macroblocks 101, 102 and 103 are encoded in sequence, and the DC coefficient of the first block of the macroblock 101 is predicted based on an initial value 128. Within the macroblock, the DC coefficients are zigzag predicted along the direction 105. After the encoding on the final block of one macroblock is completed, the value is used for predicting a DC coefficient of the first block of the next macroblock. If the third block 106 of the macro block 102 does not require encoding, the third block 106 is skipped for the prediction of the DC coefficient of the next block. This skipping is also applied to blocks 107, 108 and 109 of the macroblock 103. A resultant DC coefficient 110 obtained after coding the macroblocks 101, 102 and 103 is used for the prediction of a DC coefficient of the first block of the subsequent macroblock.
That is, according to the conventional DC coefficient prediction method, if the coding is performed in a macroblock unit including 16.times.16 blocks having four 8.times.8 blocks, the DC prediction is performed in the zigzag direction by using the previous one DC coefficient. When the DCT is performed on a block, the DC coefficient represents the brightness of the block. Also, the brightness is similar among adjacent blocks. Thus, the DC coefficients are predicted based on the above characteristics, thereby improving the performance.
However, as shown in FIG. 1, the conventional DC coefficient prediction method uses only one particular DC coefficient for the prediction. However, since the scanning direction of FIG. 1 can not provide the optimum prediction all the times, the DC coefficient obtained from the scanning, used for the prediction, is not sufficient to improve the performance. Thus, a prediction algorithm which reflects the characteristic of the image is required.